US 12,707,029 B1Granted

Video compression using region of interest of moving objects

AssigneeAmazon Technologies, Inc.

InventorsPramod Sreenivasa, Raj Kumar Akella, Ali Rahimi, Maciej Adam Jakuc

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Abstract

Described are systems and processes for compressing image data, such as video data, based on detection of region of interests (ROIs) in the image data. Image data may be analyzed to determine moving objects and stationary objects (e.g., background) depicted in the image data. To compress the image data, the stationary objects are refreshed less frequently than moving objects. ROIs are identified in the moving objects, such as a face of a person, hands of a person, and/or objects moved by the person. Some of these ROI regions/pixels are maintained at high quality, while non-ROI regions/pixels are reduced in quality to further compress the image data. Faces are reduced in quality to obfuscate a person's identity. Multiple ROI regions may be located and then tracked simultaneously. The resulting compression may reduce storage space to store the image data and/or may reduce bandwidth needed to transmit the image data to remote devices while maintaining high quality in ROI regions.

Claims20

Dependent claims

A system, comprising:

a video camera having an overhead field of view of a surface within a materials handling facility;
one or more processors;
and
a memory storing program instructions that when executed by the one or more processors cause the one or more processors to at least:
receive video data from the video camera, the video data having a first frame rate and including a high resolution video and a low resolution video of the surface within the materials handling facility;
decode the low resolution video to identify first pixels representing moving objects and second pixels representing stationary objects;
process the second pixels in the high resolution video at a second frame rate that is lower than the first frame rate;
analyze the first pixels representing the moving objects to identify:
third pixels representing regions of interest (ROI) within the moving objects, the ROI including at least hands of a person;
and
fourth pixels selected from the first pixels and excluding the third pixels, the fourth pixels representing regions of disinterest (ROD) within the moving objects;
generate high resolution frames by compositing the third pixels and the fourth pixels at the first frame rate from the high resolution video and the fourth pixels refreshed at the second frame rate;
encode the high resolution frames to create compressed video at the first frame rate that includes:
the fourth pixels representing the ROD compressed to a low quality;
the third pixels representing the ROI with a high quality;
and
the second pixels processed at the second frame rate;
and
send the compressed video from the materials handling facility to an external site for analysis of the ROI in context of the ROD and the stationary objects.

16 more elements

A method, comprising:

receiving image data including at least a high resolution video and a low resolution video at a first frame rate from one or more image capture devices located within a materials handling facility;
processing the low resolution video to identify at least a first region as including moving objects and at least a second region as including stationary objects;
processing the at least the second region at a second frame rate that is lower than the first frame rate;
analyzing the at least the first region to identify:
at least one region of interest (ROI) within the moving objects, the at least one ROI including at least one of a portion of a person or an object;
and
a region of disinterest (ROD), the ROD including remaining imagery in the first region while excluding the at least one ROI;
generating high resolution frames by compositing the at least one ROI and the ROD at the first frame rate from the high resolution video and the at least the second region refreshed at the second frame rate;
and
encoding a compressed video at a high resolution at the first frame rate that includes:
the at least one ROI with a high quality;
the ROD compressed to a low quality;
and
the at least the second region processed at a second frame rate that is lower than the first frame rate.

11 more elements

A computer-implemented method, comprising:

receiving image data including at least a high resolution video and a low resolution video at a first frame rate from the one or more image capture devices;
processing the low resolution video to identify first pixels as including moving objects and second pixels as including stationary objects;
processing the second pixels at a second frame rate that is lower than the first frame rate;
identifying, from the first pixels, a region of interest (ROI), the ROI depicting at least one of a portion of a person or an object;
designating, from the first pixels, third pixels that exclude the ROI;
and
generating high resolution frames by compositing the ROI and the third pixels at the first frame rate from the high resolution video and the second pixels refreshed at the second frame rate;
generating a compressed video at a high resolution at the first frame rate that includes:
the ROI maintaining a high quality;
the third pixels compressed to a low quality;
and
the second pixels processed at the second frame rate.

9 more elements

Dependencies are inferred from the claim text.

Facts

Application: 18/618,359Filed 27 Mar 2024
Granted: 11 Aug 2026
Term ends: Not estimatedThe source records don’t support an estimate.

Classification16 codes

H04N 7/183
Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast: for receiving images from a single remote source
G06V 10/25
Image preprocessing: determination of region of interest [ROI] or a volume of interest [VOI]
G06V 10/82
Using pattern recognition or machine learning: using neural networks
G06V 20/52
Context or environment of the image: surveillance or monitoring of activities, e.g. for recognising suspicious objects